CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Financial services: Develop credit risk models. from 2022 to 2028.

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Predictive Analytics Analytics Predictive Modeling Forecasting 145

IBM Big Data Hub

JANUARY 25, 2024

Yet many AI creators are currently facing backlash for the biases, inaccuracies and problematic data practices being exposed in their models. The math demonstrates a powerful truth All predictive models, including AI, are more accurate when they incorporate diverse human intelligence and experience.

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Predictive Modeling Modeling Risk Statistics 91

DataRobot Blog

JUNE 3, 2022

The influence of the GPT-3 language model has the potential to be both beneficial and misused. . Generative Pre-trained Transformer 3 (GPT-3) is a language model that utilizes deep-structured learning to predict human-like text. What is GPT-3? For example, an article from The Guardian, A robot wrote this entire article.

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Risk Predictive Modeling Modeling Technology 52

O'Reilly on Data

MAY 18, 2020

This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. All predictive models are wrong at times?—just

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CIO Business Intelligence

DECEMBER 11, 2023

Traditionally, the work of the CFO and the finance team was focused on protecting the company’s assets and reputation and guarding against risk. They can even optimize capital allocation decisions, such as dividend distribution versus share buy-back, by rapidly modeling multiple scenarios and market conditions.

Finance 105

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IBM Big Data Hub

MARCH 7, 2023

The challenge was gleaning relevant insights from the vast amount of data collected to help identify those infants at risk. The specific approach we took required the use of both AI and edge computing to create a predictive model that could process years of anonymized data to help doctors make informed decisions.

Risk 52

Risk Technology Informatics Predictive Modeling 52

BizAcuity

APRIL 1, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. For predictive analytics to deliver high accuracy, a lot depends on the combination of domain knowledge and technical expertise.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

FineReport

APRIL 9, 2024

From advanced analytics to predictive modeling, the evolving landscape of business intelligence is revolutionizing how data is processed and leveraged for actionable insights. The latest trends in business intelligence are reshaping the way organizations utilize data to gain a strategic advantage.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

BizAcuity

JANUARY 18, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. Predictive Analytics. Predictive Analytics can help businesses in reducing risk (eg.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

IBM Big Data Hub

MAY 18, 2023

This report outlines the combination of traditional decision automation tools with machine learning models and other technologies. As Forrester notes in the report, many organizations are eager to harness the power of AI but also must be cautious of risks.

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Reporting Scorecard Predictive Modeling Machine Learning 95

Smarten

MAY 31, 2022

The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ It is meant to identify crucial relationships and opportunities and risks and help the organization to accurately predict: Growth.

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Smart Data Collective

MARCH 3, 2021

When the risk of recurrence for a malpractice case is high, for example, they can convince the judge to be more generous in rewarding the client. The legal sector is still in its infancy when it comes to big data and analytics. Are they still legal experts if they use a computer? How can personal injury companies use analytics?

Analytics 129

Analytics Big Data Predictive Modeling Insurance 129

Smarten

SEPTEMBER 28, 2022

Gartner has predicted that, ‘Overall analytics adoption will increase from 35% to 50%, driven by vertical and domain-specific augmented analytics solutions.’ Predictive analytics uses sophisticated analytical methodologies to predict future outcomes based on historical data. Customer Churn. Quality Control. Demand Planning.

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Predictive Analytics Analytics Predictive Modeling Forecasting 52

Cloudera

JUNE 27, 2023

Adopting an MDA is more efficient and cost effective than legacy data architectures which are siloed, poorly governed, with vast redundant data sets and data processes that are expensive and expose the company to risk. Appliance-based models are usually significantly more expensive than disaggregated solutions. Modernize data flows.

Data Architecture 63

Data Architecture Predictive Modeling Data Governance Data-driven 63

IBM Big Data Hub

MAY 1, 2023

The early versions of AI were capable of predictive modelling (e.g., The four categories of predictive modelling, robotics, speech and image recognition are collectively known as algorithm-based AI or Discriminative AI. It is used to return a prediction or result based on conditional probability.

Insurance 83

Insurance Predictive Modeling Cost-Benefit Statistics 83

DataKitchen

JUNE 19, 2023

Our customers start looking at the data in dashboards and models and then find many issues. Perhaps we could just chill out in those stressful situations and “let go,” as the Buddha suggests. The spiritual benefits of letting go may be profound, but finding and fixing the problem at its root is, as Samuel Florman writes, “ existential joy.”

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Testing Cost-Benefit Metrics Data Quality 130

Smart Data Collective

SEPTEMBER 17, 2020

Here are a few of the advantages of Big Data in the banking and financial industry: Improvement in risk management operations. Big Data can efficiently enhance the ways firms utilize predictive models in the risk management discipline. Big Data provides financial and banking organizations with better risk coverage.

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Big Data Finance Risk Management Risk 142

CIO Business Intelligence

OCTOBER 5, 2023

We’ve seen so many initiatives fail when it’s technology for technology’s sake,” says Davé, who suggests two means of avoiding this mistake: prioritization models aligned to your business strategy and strategic partnerships. Let’s start with the models. For AI, the high-value quadrant is where you’ll find most predictive modeling.

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Experimentation Strategy Machine Learning Interactive 130

DataRobot

OCTOBER 19, 2021

By leveraging prediction and augmented decision-making, governments can address the needs of taxpayers proactively while quickly adapting to evolving circumstances. DataRobot helped combat this problem head on by applying AI to evaluate and predict resource allocation and identify the most impacted communities from a national to county level.

Forecasting 98

Forecasting Predictive Modeling Optimization Testing 98

CIO Business Intelligence

OCTOBER 12, 2023

Generac Power Systems’ Tim Dickson is an award-winning CIO who drives transformative change through technology and talent. He’s known as a digital game changer who operates at the intersection of advanced technology and business strategy. What’s your take on the changing role of the CIO? Tim Dickson: I have a funny story that sort of encompasses it.

IoT 126

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Smart Data Collective

MARCH 23, 2022

This AI could be utilized as a safety feature , like real-time risk assessment, for example, alerting the driver when a potential incident has been detected. Utilizing advanced heuristics and AI modeling OEMs can simulate a multitude of conditions, fast-tracking these models using automation. How do they make vehicles safer?

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IoT Internet of Things Testing Cost-Benefit 111

CIO Business Intelligence

OCTOBER 13, 2023

Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Ontotext

MAY 31, 2023

To support drug discovery, Ontotext has recently developed a method for gene-disease link prediction, which can help focus research efforts where it would matter most and speed up the drug development process. The link prediction models are based on the so-called Knowledge Graph Embeddings, which relying on knowledge graph technology.

Experimentation 52

Experimentation Cost-Benefit Predictive Modeling Risk 52

DataRobot

MARCH 2, 2021

With DataRobot, you can build dozens of predictive models with the push of a button and easily deploy them. Monitoring deployed models is easy because we provide features to check on service health, data drift, and accuracy. Every day, millions of people interact with AI systems, often without knowing it. Our Program.

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Smarten

MARCH 12, 2020

A solution that provides a balance between data agility and access and data governance and security can provide solid, dependable information and the ability for users to leverage Self-Serve Data Preparation , Assisted Predictive Modeling and Smart Data Visualization while protecting the organization from risk and mitigating security issues.

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CIO Business Intelligence

DECEMBER 13, 2022

Our digital transformation strategy is centered around establishing a consumer-oriented model that helps us customize chronic care management based on the ever-changing conditions of each patient.” Here, IT is playing a significant role. A lot of innovation initiatives right now are small and more closely aligned with tangible results.

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Strategy Technology Digital Transformation Data Lake 98

Smarten

JUNE 8, 2022

Citizen Data Scientists can create new models, share models and collaborate, thereby improving business results and data literacy.’. Predicting Demand. According to technology research firm, Gartner, the number of Citizen Data Scientists will grow at five times the rate of traditional data scientists. Analyzing Customer Churn.

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Predictive Analytics Predictive Modeling Forecasting Optimization 52

John Wheeler

OCTOBER 20, 2020

We continue our “20 for 20” theme this year by highlighting the integrated risk management (IRM) critical capabilities and top 20 software functions / features. These five capabilities support both integrated view of strategic, operational and technology risk as well as the related business outcomes, processes and assets.

Risk Management 52

Risk Management Risk Predictive Modeling Insurance 52

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.

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Business Over Broadway

SEPTEMBER 27, 2018

pharmacogenomics) and risk assessment of genetic disorders (e.g., In this scenario, marketing analytics can only be conducted within one data silo at a time, decreasing your model’s predictive power / increasing your model’s error. Machine Learning and Predictive Modeling of Customer Churn.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

Domino Data Lab

JULY 28, 2021

There are many software packages that allow anyone to build a predictive model, but without expertise in math and statistics, a practitioner runs the risk of creating a faulty, unethical, and even possibly illegal data science application. All models are not made equal.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

IBM Big Data Hub

OCTOBER 5, 2022

Build planning models to improve supply chain management. You also build planning models to capture relationships and constraints so that you can change your driver assumptions and immediately see the impact on resources and capacity over time. The challenge faced by every company is matching supply with demand.

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Analytics Forecasting Predictive Modeling Manufacturing 52

IBM Big Data Hub

FEBRUARY 14, 2024

Other uses include Netflix offering viewing recommendations powered by models that process data sets collected from viewing history; LinkedIn uses ML to filter items in a newsfeed, making employment recommendations and suggestions on who to connect with; and Spotify uses ML models to generate its song recommendations.

Cost-Benefit 88

Cost-Benefit Insurance Unstructured Data Machine Learning 88

IBM Big Data Hub

MAY 6, 2024

Enter the age of data-driven protocol assessment: using benchmarking tools and predictive modeling to gauge protocol intricacies and forecast eligible patient numbers, which then inform protocol adjustments. The latest developments in large language models (LLMs) have the potential to significantly expedite protocol design processes.

Advertising 57

Advertising Data-driven Optimization Strategy 57

Smarten

APRIL 17, 2018

How Can Assistive Predictive Modeling Help My Business Users? In order to achieve goals and objectives and perform well in their respective roles, business users need to analyze data, draw conclusions, predict results and help the organization achieve its goals. If you want to find out more, Contact Us.

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Smarten

MAY 17, 2019

There is a lot of information within your enterprise, and being able to analyze that information is crucial to decision-making and to managing your business and predicting results with efficiency and accuracy. View the Predictive Analytics Using External Data Use Case Slide Share. Customer Targeting. Customer Churn. Fraud Mitigation.

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Predictive Analytics Analytics Predictive Modeling Risk Management 58

IBM Big Data Hub

JUNE 29, 2023

When a critical asset like an expensive piece of machinery or infrastructure breaks unexpectedly, it affects customers and can cost companies millions. To be successful, businesses need to have clear, real-time visibility into the condition of their assets and a plan to keep them running smoothly and make repairs quickly when things break.

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